Dataset Information

Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine.

ABSTRACT:

Aims/hypothesis

Individualised variable-interval risk-based screening offers better targeting and improved cost-effectiveness in screening for diabetic retinopathy. We developed a generalisable risk calculation engine (RCE) to assign personalised intervals linked to local population characteristics, and explored differences in assignment compared with current practice.

Methods

Data from 5 years of photographic screening and primary care for people with diabetes, screen negative at the first of > 1 episode, were combined in a purpose-built near-real-time warehouse. Covariates were selected from a dataset created using mixed qualitative/quantitative methods. Markov modelling predicted progression to screen-positive (referable diabetic retinopathy) against the local cohort history. Retinopathy grade informed baseline risk and multiple imputation dealt with missing data. Acceptable intervals (6, 12, 24 months) and risk threshold (2.5%) were established with patients and professional end users.

Results

Data were from 11,806 people with diabetes (46,525 episodes, 388 screen-positive). Covariates with sufficient predictive value were: duration of known disease, HbA_1c, age, systolic BP and total cholesterol. Corrected AUC (95% CIs) were: 6 months 0.88 (0.83, 0.93), 12 months 0.90 (0.87, 0.93) and 24 months 0.91 (0.87, 0.94). Sensitivities/specificities for a 2.5% risk were: 6 months 0.61, 0.93, 12 months 0.67, 0.90 and 24 months 0.82, 0.81. Implementing individualised RCE-based intervals would reduce the proportion of people becoming screen-positive before the allocated screening date by > 50% and the number of episodes by 30%.

Conclusions/interpretation

The Liverpool RCE shows sufficient performance for a local introduction into practice before wider implementation, subject to external validation. This approach offers potential enhancements of screening in improved local applicability, targeting and cost-effectiveness.

SUBMITTER: Eleuteri A

PROVIDER: S-EPMC6448900 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine.

Eleuteri Antonio A Fisher Anthony C AC Broadbent Deborah M DM García-Fiñana Marta M Cheyne Christopher P CP Wang Amu A Stratton Irene M IM Gabbay Mark M Seddon Daniel D Harding Simon P SP

Diabetologia 20170824 11

<h4>Aims/hypothesis</h4>Individualised variable-interval risk-based screening offers better targeting and improved cost-effectiveness in screening for diabetic retinopathy. We developed a generalisable risk calculation engine (RCE) to assign personalised intervals linked to local population characteristics, and explored differences in assignment compared with current practice.<h4>Methods</h4>Data from 5 years of photographic screening and primary care for people with diabetes, screen negative at ...[more]

PMID: 28840258

Similar Datasets

Project description:Importance:To prevent blindness, repeated infant eye examinations are performed to detect severe retinopathy of prematurity (ROP), yet only a small fraction of those screened need treatment. Early individual risk stratification would improve screening timing and efficiency and potentially reduce the risk of blindness. Objectives:To create and validate an easy-to-use prediction model using only birth characteristics and to describe a continuous hazard function for ROP treatment. Design, Setting, and Participants:In this retrospective cohort study, Swedish National Patient Registry data from infants screened for ROP (born between January 1, 2007, and August 7, 2018) were analyzed with Poisson regression for time-varying data (postnatal age, gestational age [GA], sex, birth weight, and important interactions) to develop an individualized predictive model for ROP treatment (called DIGIROP-Birth [Digital ROP]). The model was validated internally and externally (in US and European cohorts) and compared with 4 published prediction models. Main Outcomes and Measures:The study outcome was ROP treatment. The measures were estimated momentary and cumulative risks, hazard ratios with 95% CIs, area under the receiver operating characteristic curve (hereinafter referred to as AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results:Among 7609 infants (54.6% boys; mean [SD] GA, 28.1 [2.1] weeks; mean [SD] birth weight, 1119 [353] g), 442 (5.8%) were treated for ROP, including 142 (40.1%) treated of 354 born at less than 24 gestational weeks. Irrespective of GA, the risk for receiving ROP treatment increased during postnatal weeks 8 through 12 and decreased thereafter. Validations of DIGIROP-Birth for 24 to 30 weeks' GA showed high predictive ability for the model overall (AUC, 0.90 [95% CI, 0.89-0.92] for internal validation, 0.94 [95% CI, 0.90-0.98] for temporal validation, 0.87 [95% CI, 0.84-0.89] for US external validation, and 0.90 [95% CI, 0.85-0.95] for European external validation) by calendar periods and by race/ethnicity. The sensitivity, specificity, PPV, and NPV were numerically at least as high as those obtained from CHOP-ROP (Children's Hospital of Philadelphia-ROP), OMA-ROP (Omaha-ROP), WINROP (weight, insulinlike growth factor 1, neonatal, ROP), and CO-ROP (Colorado-ROP), models requiring more complex postnatal data. Conclusions and Relevance:This study validated an individualized prediction model for infants born at 24 to 30 weeks' GA, enabling early risk prediction of ROP treatment based on birth characteristics data. Postnatal age rather than postmenstrual age was a better predictive variable for the temporal risk of ROP treatment. The model is an accessible online application that appears to be generalizable and to have at least as good test statistics as other models requiring longitudinal neonatal data not always readily available to ophthalmologists.

Project description:It is a global challenge to provide regular retinal screening for all people with diabetes to detect sight-threatening diabetic retinopathy (STDR). To determine if circulating biomarkers could be used to prioritize people with type 2 diabetes for retinal screening to detect STDR. This cross-sectional study collected data from October 22, 2018, to December 31, 2021. All laboratory staff were masked to the clinical diagnosis, assigned a study cohort, and provided with the database containing the clinical data. This was a multicenter study conducted in parallel in 3 outpatient ophthalmology clinics in the UK and 2 centers in India. Adults 40 years and older were categorized into 4 groups: (1) no history of diabetes, (2) type 2 diabetes of at least 5 years' duration with no evidence of DR, (3) nonproliferative DR with diabetic macular edema (DME), or (4) proliferative DR. STDR comprised groups 3 and 4. Thirteen previously verified biomarkers were measured using enzyme-linked immunosorbent assay. Severity of DR and presence of DME were diagnosed using fundus photographs and optical coherence tomography. Weighted logistic regression and receiver operating characteristic curve analysis (ROC) were performed to identify biomarkers that discriminate STDR from no DR beyond the standard clinical parameters of age, disease duration, ethnicity (in the UK) and hemoglobin A1c. A total of 538 participants (mean [SD] age, 60.8 [9.8] years; 319 men [59.3%]) were recruited into the study. A total of 264 participants (49.1%) were from India (group 1, 54 [20.5%]; group 2, 53 [20.1%]; group 3, 52 [19.7%]; group 4, 105 [39.8%]), and 274 participants (50.9%) were from the UK (group 1, 50 [18.2%]; group 2, 70 [25.5%]; group 3, 55 [20.1%]; group 4, 99 [36.1%]). ROC analysis (no DR vs STDR) showed that in addition to age, disease duration, ethnicity (in the UK) and hemoglobin A1c, inclusion of cystatin C had near-acceptable discrimination power in both countries (area under the receiver operating characteristic curve [AUC], 0.779; 95% CI, 0.700-0.857 in 215 patients in the UK with complete data; AUC, 0.696; 95% CI, 0.602-0.791 in 208 patients in India with complete data). Results of this cross-sectional study suggest that serum cystatin C had good discrimination power in the UK and India. Circulating cystatin-C levels may be considered as a test to identify those who require prioritization for retinal screening for STDR.

Project description:BACKGROUND:Internationally, systematic screening for sight-threatening diabetic retinopathy (STDR) usually includes annual recall. Researchers and policy-makers support extending screening intervals, citing evidence from observational studies with low incidence rates. However, there is little research around the acceptability to people with diabetes (PWD) and health care professionals (HCP) about changing eye screening intervals. METHODS:We conducted a qualitative study to explore issues surrounding acceptability and the barriers and enablers for changing from annual screening, using in-depth, semistructured interviews analysed using the constant comparative method. PWD were recruited from general practices and HCP from eye screening networks and related specialties in North West England using purposive sampling. Interviews were conducted prior to the commencement of and during a randomised controlled trial (RCT) comparing fixed annual with variable (6, 12 or 24?month) interval risk-based screening. RESULTS:Thirty PWD and 21 HCP participants were interviewed prior to and 30 PWD during the parallel RCT. The data suggests that a move to variable screening intervals was generally acceptable in principle, though highlighted significant concerns and challenges to successful implementation. The current annual interval was recognised as unsustainable against a backdrop of increasing diabetes prevalence. There were important caveats attached to acceptability and a need for clear safeguards around: the safety and reliability of calculating screening intervals, capturing all PWD, referral into screening of PWD with diabetic changes regardless of planned interval. For PWD the 6-month interval was perceived positively as medical reassurance, and the 12-month seen as usual treatment. Concerns were expressed by many HCP and PWD that a 2-year interval was too lengthy and was risky for detecting STDR. There were also concerns about a negative effect upon PWD care and increasing non-attendance rates. Amongst PWD, there was considerable conflation and misunderstanding about different eye-related appointments within the health care system. CONCLUSIONS:Implementing variable-interval screening into clinical practice is generally acceptable to PWD and HCP with important caveats, and misconceptions must be addressed. Clear safeguards against increasing non-attendance, loss of diabetes control and alternative referral pathways are required. For risk calculation systems to be safe, reliable monitoring and clear communication is required.

Project description:BackgroundAccumulating evidence has suggested a link between adipokines and diabetic retinopathy (DR). This study is aimed at investigating the risk factors for sight-threatening DR (STDR) and establishing a prognostic model for predicting STDR among a high-risk population of patients with type 2 diabetes mellitus (T2DM).MethodsPlasma concentrations of adipokines were determined by enzyme-linked immunosorbent assay. In the case-control set, principal component analysis (PCA) was performed to select optimal predictive cytokines for STDR, involving severe nonproliferative DR (NPDR) and proliferative DR. Support vector machine (SVM) was used to examine the possible combination of baseline plasma adipokines to discriminate the patients with mild NPDR who will later develop STDR. An individual prospective cohort with a follow-up period of 3 years was used for the external validation.ResultsIn both training and testing sets, involving 306 patients with T2DM, median levels of plasma adiponectin (APN), leptin, and fatty acid-binding protein 4 (FABP4) were significantly higher in the STDR group than those in mild NPDR. Except for adipsin, the other three adipokines, FABP4, APN, and leptin, were selected by PCA and integrated into SVM. The accuracy of the multivariate SVM classification model was acceptable in both the training set (AUC = 0.81, sensitivity = 71%, and specificity = 91%) and the testing set (AUC = 0.77, sensitivity = 61%, and specificity = 92%). 110 T2DM patients with mild NPDR, the high-risk population of STDR, were enrolled for external validation. Based on the SVM, the risk of each patient was calculated. More STDR occurred in the high-risk group than in the low-risk group, which were grouped by the median value of APN, FABP4, and leptin, respectively. The model was validated in an individual cohort using SVM with the AUC, sensitivity, and specificity reaching 0.77, 64%, and 91%, respectively.ConclusionsAdiponectin, leptin, and FABP4 were demonstrated to be associated with the severity of DR and maybe good predictors for STDR, suggesting that adipokines may play an important role in the pathophysiology of DR development.

Project description:To report the prevalence of all grades of diabetic retinopathy and associations with demographic, clinical and biochemical variables in people with diabetes in Southern Malawi.We report baseline data from a 24-month prospective cohort study. Subjects were systematically sampled from two hospital-based, primary care diabetes clinics. Visual acuity, glycaemic control, systolic blood pressure, HIV status, urine albumin-creatinine ratio, and haemoglobin and serum lipid levels were assessed. Retinopathy was graded at an accredited reading centre using modified Wisconsin grading of four-field mydriatic photographs.A total of 357 subjects were studied. Of these, 13.4% subjects were HIV-positive and 15.1% had anaemia. The overall prevalence rates of any retinopathy, sight-threatening diabetic retinopathy and proliferative retinopathy were 50.1% (95% CI 44.9-55.3), 29.4% (95% CI 24.7-34.1) and 7.3% (95% CI 4.6-10.0), respectively. In multivariate logistic analysis the presence of sight-threatening retinopathy was associated with duration of diabetes (odds ratio 1.11, 95% CI 1.05-1.17), HbA1c (odds ratio 1.31, 95% CI 1.13-1.50), systolic blood pressure (odds ratio 1.03, 95% CI 1.01-1.04), haemoglobin (odds ratio 0.98, 95% CI 0.96-0.99) and LDL cholesterol (odds ratio 1.63, 95% CI 1.18-2.25). No significant association with HIV status was observed. In all, 3.6 and 1.4% of people in our study cohort had visual acuity worse than 6/18 and 6/60 in the better eye, respectively.The present study found a prevalence of sight-threatening retinopathy in diabetes clinics in one Sub-Saharan African country of approximately four times that reported in recent European studies and a prevalence of proliferative retinopathy approximately 10 times higher. The association of sight-threatening retinopathy with lower haemoglobin level is a new finding. Our results highlight the urgent need for provision of services for retinopathy detection and management to avoid a large burden of vision loss.

Dataset Information

Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine.

Aims/hypothesis

Methods

Results

Conclusions/interpretation

Publications

Individualised variable-interval risk-based screening for sight-threatening diabetic retinopathy: the Liverpool Risk Calculation Engine.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets